mirror of https://github.com/databricks/cli.git
50 lines
1.8 KiB
Cheetah
50 lines
1.8 KiB
Cheetah
# {{.project_name}}
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The '{{.project_name}}' project was generated by using the default-python template.
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## Getting started
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1. Install the Databricks CLI from https://docs.databricks.com/dev-tools/cli/databricks-cli.html
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2. Authenticate to your Databricks workspace, if you have not done so already:
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```
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$ databricks configure
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```
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3. To deploy a development copy of this project, type:
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```
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$ databricks bundle deploy --target dev
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```
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(Note that "dev" is the default target, so the `--target` parameter
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is optional here.)
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This deploys everything that's defined for this project.
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For example, the default template would deploy a job called
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`[dev yourname] {{.project_name}}_job` to your workspace.
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You can find that job by opening your workpace and clicking on **Workflows**.
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4. Similarly, to deploy a production copy, type:
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```
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$ databricks bundle deploy --target prod
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```
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Note that the default job from the template has a schedule that runs every day
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(defined in resources/{{.project_name}}_job.yml). The schedule
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is paused when deploying in development mode (see
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https://docs.databricks.com/dev-tools/bundles/deployment-modes.html).
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5. To run a job or pipeline, use the "run" command:
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```
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$ databricks bundle run
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```
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6. Optionally, install developer tools such as the Databricks extension for Visual Studio Code from
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https://docs.databricks.com/dev-tools/vscode-ext.html.
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{{- if (eq .include_python "yes") }} Or read the "getting started" documentation for
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**Databricks Connect** for instructions on running the included Python code from a different IDE.
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{{- end}}
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7. For documentation on the Databricks asset bundles format used
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for this project, and for CI/CD configuration, see
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https://docs.databricks.com/dev-tools/bundles/index.html.
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